An image sensor converts a visual image to digital data that may be represented by a picture. The image sensor comprises an array of pixels, which are unit devices for the conversion of the visual image into the digital data. Digital cameras and optical imaging devices employ an image sensor. Image sensors include charge-coupled devices (CCDs) or complementary metal oxide semiconductor (CMOS) image sensors.
While CMOS image sensors have been more recently developed compared to the CCDs, CMOS image sensors provide an advantage of lower power consumption, smaller size, and faster data processing than CCDs as well as direct digital output that is not available in CCDs. Also, CMOS image sensors have lower manufacturing cost compared with the CCDs since many standard semiconductor manufacturing processes may be employed to manufacture CMOS image sensors. For these reasons, commercial employment of CMOS image sensors has been steadily increasing in recent years.
Since each image sensor pixel needs to be located at a unique position within the array, replacement of a non-functional image sensor pixel is difficult. Thus, it is imperative to achieve a defect-free array for a commercially viable manufacture of CMOS image sensors.
Typically, monitoring of semiconductor manufacturing processes is facilitated by small test structure in a scribe area, or a “KERF” area, which is a small area outside the area of a product chip. The test structure is tested early on during the manufacturing sequence prior to a final test so that any process deviations in the manufacturing processes may be detected early on, and to provide a fast feedback mechanism to the manufacturing processes without waiting for the results from the final test.
While placement of an image sensor structure in the test structure provides some early feedback on the manufacturing processes, the information derived from such an image sensor is likely to be inadequate because defect generation may be a statistical process and the image sensor structure in the test structure may not adequately reproduce defects that may be present in an image sensor array in a product chip. In other words, discrete image sensor structures may not be able to provide enough sampling of the defects when the nature of defects is statistical. Parameters of one image sensor or several image sensors do not reliably predict the statistical operation of an array of image sensors containing on the order of 1 million image sensor pixels. Further, external drive/readback circuits have significant influence on device performance, for example, by a non-negligible level of leakage current. In addition, image sensors are analog devices that do not lend themselves amenable to built-in-self-test (BIST) or other standard test access methods. Despite the above mentioned difficulties in testing, however, detection of such process defects in a timely manner is critical in an economically viable manufacturing of a semiconductor chip containing a CMOS image sensor array.
In view of the above, there exists a need for a method of monitoring process defects that are statistical in nature. Further, there exists a need for a design structure for providing sufficiently sensitive monitoring of process defects that may be detected only statistically. Yet further, there exists a need for a structure for providing such sensitive monitoring of process defects.
In addition, different types of image sensor pixels may be employed among different semiconductor chips. Thus, there exists a need to provide a test structure incorporating the same type of image sensor as the image sensors employed in a semiconductor chip on the same semiconductor substrate, a method of generating a design structure for the same, and a method of monitoring process defects employing the same.